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The continuous displacive phase transition in SrTiO$_3$ near $T_c \approx 105$ K features a central elastic peak in neutron scattering investigations at temperatures above $T_c$, i.e., before the corresponding soft phonon mode is overdamped upon cooling. The origin of this central peak is still not understood. Here, we report an inelastic x-ray scattering investigation of the cubic-to-tetragonal phase transition in SrTiO$_3$. We compare quantitatively measurements of the soft phonon mode on two differently grown samples and discuss the findings regarding results from thermodynamic probes such as specific heat and thermal conductivity. Furthermore, we use inelastic x-ray scattering to perform elastic scans with both high momentum- and milli-electronvolt energy-resolution and, thus, be able to separate elastic intensities of the central peak from low-energy quasielastic phonon scattering. Our results indicate that the evolution of the soft mode is similar in both samples though the intensities of the central peak differ by a factor of four. Measurements revealing anisotropic correlation lengths on cooling towards $T_c$, indicate that local properties of the crystals to which collective lattice excitations are insensitive are likely at the origin of the central elastic line in SrTiO$_3$., Comment: Manuscript contains 8 pages, 4 figures. Supplementary information contains 26 pages, 13 figures

High-dimensional entanglement is a valuable resource for several quantum information processing tasks, and is often characterized by the Schmidt number and specific classes of entangled states beyond qubit-qubit and qubit-qutrit systems. We propose a criterion to detect high-dimensional entanglement, focusing on determining the Schmidt number of quantum states and identifying significant classes of PPT and NPT entangled states. Our approach relies on evaluating moments of generalized positive maps which can be efficiently simulated in real experiments without the requirement of full-state tomography. We demonstrate the effectiveness of our detection scheme through various illustrative examples. As a direct application, we explore the implications of our moment-based detection schemes in identifying useful quantum channels such as non-Schmidt number breaking channels and non-entanglement breaking channels. Finally, we present the operational implication of our proposed moment criterion through its manifestation in channel discrimination tasks., Comment: Initial draft, 14 pages, 1 Table

Two-dimensional twisted bilayer moir\'e structures provide a versatile material platform for realizing a rich variety of strongly correlated electronic quantum phases intricately coupled with the periodically modulated lattice structures. In this work, we use ultrafast electron diffraction to directly reveal the photoinduced dynamic evolution of the moir\'e superlattice in $2^\circ$ and $57^\circ$ twisted WSe$_2$/MoSe$_2$ heterobilayers. Upon above-band-gap photoexcitation, the moir\'e superlattice diffraction features are enhanced within 1 ps and subsequently suppressed several picoseconds after, accompanied by a collective lattice excitation of a moir\'e phonon mode with sub-THz frequency. This unique response deviates markedly from typical photoinduced lattice heating, and suggests dynamic twisting and untwisting of the local moir\'e chiral structure. We infer large oscillations in the local twist angle, approaching $1^\circ$ peak to trough, that are driven by ultrafast charge carrier excitation and relaxation -- a phenomenon further supported by molecular dynamics simulations. Our findings suggest a novel approach for real-time dynamic reconfiguration of moire superlattices to achieve ultrafast modulation of their strongly correlated behaviors.

The multi-stage method of laser wakefield acceleration (LWFA) presents a promising approach for developing stable, full-optical, high-energy electron accelerators. By segmenting the acceleration process into several booster stages, each powered by independent laser drivers, this technique effectively mitigates challenges such as electron dephasing, pump depletion, and laser diffraction. A critical aspect of multi-stage LWFA is the nonlinear interaction between the injected electron beam and the laser-driven wakefields in the booster stage. This study investigates the injection and acceleration of external electron beams within wakefields in the booster stage using multi-dimensional Particle-In-Cell (PIC) simulations. We provide both qualitative and quantitative descriptions of the observed physical processes. Key parameters influencing charge coupling process and the resultant beam quality have been identified. Furthermore, we have examined how off-axis injection relative to the driver laser influences the acceleration process and beam quality. Our findings provide valuable insights for advancing and optimizing multi-stage plasma-based accelerators., Comment: 15 pages, 8 figures, Accepted in Journal of Physics D: Applied Physics

In this paper, we study the parameterized complexity of the MaxMin versions of two fundamental separation problems: Maximum Minimal $st$-Separator and Maximum Minimal Odd Cycle Transversal (OCT), both parameterized by the solution size. In the Maximum Minimal $st$-Separator problem, given a graph $G$, two distinct vertices $s$ and $t$ and a positive integer $k$, the goal is to determine whether there exists a minimal $st$-separator in $G$ of size at least $k$. Similarly, the Maximum Minimal OCT problem seeks to determine if there exists a minimal set of vertices whose deletion results in a bipartite graph, and whose size is at least $k$. We demonstrate that both problems are fixed-parameter tractable parameterized by $k$. Our FPT algorithm for Maximum Minimal $st$-Separator answers the open question by Hanaka, Bodlaender, van der Zanden and Ono (TCS 2019). One unique insight from this work is the following. We use the meta-result of Lokshtanov, Ramanujan, Saurabh and Zehavi (ICALP 2018) that enables us to reduce our problems to highly unbreakable graphs. This is interesting, as an explicit use of the recursive understanding and randomized contractions framework of Chitnis, Cygan, Hajiaghayi, Pilipczuk and Pilipczuk (SICOMP 2016) to reduce to the highly unbreakable graphs setting (which is the result that Lokshtanov et al. tries to abstract out in their meta-theorem) does not seem obvious because certain ``extension'' variants of our problems are W[1]-hard., Comment: Accepted to STACS 2025

We study the problem of missing not at random (MNAR) datasets with binary outcomes. We propose an exponential tilt based approach that bypasses any knowledge on 'nonresponse instruments' or 'shadow variables' that are usually required for statistical estimation. We establish a sufficient condition for identifiability of tilt parameters and propose an algorithm to estimate them. Based on these tilt parameter estimates, we propose importance weighted and doubly robust estimators for any mean functions of interest, and validate their performances in a synthetic dataset. In an experiment with the Waterbirds dataset, we utilize our tilt framework to perform unsupervised transfer learning, when the responses are missing from a target domain of interest, and achieve a prediction performance that is comparable to a gold standard.

One of the most basic problems in reinforcement learning (RL) is policy evaluation: estimating the long-term return, i.e., value function, corresponding to a given fixed policy. The celebrated Temporal Difference (TD) learning algorithm addresses this problem, and recent work has investigated finite-time convergence guarantees for this algorithm and variants thereof. However, these guarantees hinge on the reward observations being always generated from a well-behaved (e.g., sub-Gaussian) true reward distribution. Motivated by harsh, real-world environments where such an idealistic assumption may no longer hold, we revisit the policy evaluation problem from the perspective of adversarial robustness. In particular, we consider a Huber-contaminated reward model where an adversary can arbitrarily corrupt each reward sample with a small probability $\epsilon$. Under this observation model, we first show that the adversary can cause the vanilla TD algorithm to converge to any arbitrary value function. We then develop a novel algorithm called Robust-TD and prove that its finite-time guarantees match that of vanilla TD with linear function approximation up to a small $O(\epsilon)$ term that captures the effect of corruption. We complement this result with a minimax lower bound, revealing that such an additive corruption-induced term is unavoidable. To our knowledge, these results are the first of their kind in the context of adversarial robustness of stochastic approximation schemes driven by Markov noise. The key new technical tool that enables our results is an analysis of the Median-of-Means estimator with corrupted, time-correlated data that might be of independent interest to the literature on robust statistics., Comment: Accepted to AISTATS 2025

With the rapid growth in the number of Large Language Models (LLMs), there has been a recent interest in LLM routing, or directing queries to the cheapest LLM that can deliver a suitable response. Following this line of work, we introduce CARROT, a Cost AwaRe Rate Optimal rouTer that can select models based on any desired trade-off between performance and cost. Given a query, CARROT selects a model based on estimates of models' cost and performance. Its simplicity lends CARROT computational efficiency, while our theoretical analysis demonstrates minimax rate-optimality in its routing performance. Alongside CARROT, we also introduce the Smart Price-aware Routing (SPROUT) dataset to facilitate routing on a wide spectrum of queries with the latest state-of-the-art LLMs. Using SPROUT and prior benchmarks such as Routerbench and open-LLM-leaderboard-v2 we empirically validate CARROT's performance against several alternative routers.

The parameter convergence relies on a stringent persistent excitation (PE) condition in adaptive control. Several works have proposed a memory term in the last decade to translate the PE condition to a feasible finite excitation (FE) condition. This work proposes a combined model reference adaptive control for a class of uncertain nonlinear systems with an unknown control effectiveness vector. The closed-loop system is exponentially stable under the FE condition. The exponential rate of convergence is independent of the excitation level of the regressor vector and is lower-bounded in terms of the system parameters and user-designed gains. Numerical simulation is illustrated, validating the results obtained with the proposed adaptive control.

Efficiently distributing secret keys over long distances remains a critical challenge in the development of quantum networks. "First-generation" quantum repeater chains distribute entanglement by executing protocols composed of probabilistic entanglement generation, swapping and distillation operations. However, finding the protocol that maximizes the secret-key rate is difficult for two reasons. First, calculating the secretkey rate for a given protocol is non-trivial due to experimental imperfections and the probabilistic nature of the operations. Second, the protocol space rapidly grows with the number of nodes, and lacks any clear structure for efficient exploration. To address the first challenge, we build upon the efficient machinery developed by Li et al. [1] and we extend it, enabling numerical calculation of the secret-key rate for heterogeneous repeater chains with an arbitrary number of nodes. For navigating the large, unstructured space of repeater protocols, we implement a Bayesian optimization algorithm, which we find consistently returns the optimal result. Whenever comparisons are feasible, we validate its accuracy against results obtained through brute-force methods. Further, we use our framework to extract insight on how to maximize the efficiency of repeater protocols across varying node configurations and hardware conditions. Our results highlight the effectiveness of Bayesian optimization in exploring the potential of near-term quantum repeater chains., Comment: 8 pages, 8 figures

We study the approximation of eigenvalues and eigenfunctions for the Laplace-Beltrami operator on compact manifolds without boundary. The analysis is centered on manifolds characterized by specific geometric constraints: lower bounds on Ricci curvature and injectivity radius, and an upper bound on diameter. Using weighted graph techniques, we approximate the eigenvalues for manifolds having a uniform lower bound on the volume of small balls and also investigate uniform bounds of eigenvalues applicable across the entire class.

Question generation in education is a time-consuming and cognitively demanding task, as it requires creating questions that are both contextually relevant and pedagogically sound. Current automated question generation methods often generate questions that are out of context. In this work, we explore advanced techniques for automated question generation in educational contexts, focusing on In-Context Learning (ICL), Retrieval-Augmented Generation (RAG), and a novel Hybrid Model that merges both methods. We implement GPT-4 for ICL using few-shot examples and BART with a retrieval module for RAG. The Hybrid Model combines RAG and ICL to address these issues and improve question quality. Evaluation is conducted using automated metrics, followed by human evaluation metrics. Our results show that both the ICL approach and the Hybrid Model consistently outperform other methods, including baseline models, by generating more contextually accurate and relevant questions., Comment: Accepted at the 16th Meeting of the Forum for Information Retrieval Evaluation as a Regular Paper

An active chiral rotor is a spherical object that can generate chiral flows in a fluid by rotating about an axis. For example, if the flow around the upper hemisphere of the chiral rotor is in a clockwise direction, then the flow in the lower hemisphere is in the anti-clockwise direction, and vice versa. In this paper, we aim to study the combined behaviour of hydrodynamically interacting chiral rotors in the presence of an external chemical gradient. While a single isolated rotor is stationary in a fluid, a pair of rotors can move in linear or circular paths as they hydrodynamically interact with each other. It is observed that the emergent linear or circular trajectories depend on the type of rotors and the orientation of their rotation axes. The dynamics of the rotors are altered in a more complex environment, such as in an external chemical field. Interestingly, we observe two types of motion: chemotaxis and anti-chemotaxis. While in the anti-chemotaxis case, both rotors are driving away from the target, in the chemotaxis case, one of the rotors successfully reaches the chemical target. This study helps to understand the collective behavior of self-propelled microorganisms and artificial swimmers.

The increasing threat of uranium contamination to environmental and human health due to its radiotoxicity demands the development of novel and efficient adsorbents for remediation. In this study, we investigated the potential of poly(amidoamine) (PAMAM) dendrimers of generations 1 to 4 (G1 - G4) functionalized with graphene and carbon nanotubes (CNTs) as adsorbents for uranyl ion removal from aqueous solutions. By combining atomistic molecular dynamics (MD) simulations with experimental validation, we examined the influence of pH, uranyl ion concentration, and dendrimer generation on adsorption behavior. Our study revealed that uranyl ion adsorption is greater when PAMAM is grafted onto graphene/CNT than pristine PAMAM. However, PAMAM-grafted CNTs exhibit superior adsorption capacity at specific uranyl concentrations due to their curvature and abundant accessible binding sites. Higher-generation PAMAM dendrimers grafted onto graphene/CNTs exhibit greater adsorption capacity due to the increased availability of binding sites, which is consistent with experimental observations. The adsorption capability of uranyl ions in all four generations of the PAMAM dendrimer increased as the concentration of uranyl ions increased. Adsorption capacity increases with increasing uranyl ion concentration, and adsorption occurs on both PAMAM and graphene/CNT surfaces, with saturation observed at higher concentrations. This study provides insights into the adsorption mechanisms and highlights the potential of PAMAM-based nanocomposites for efficient uranyl ion extraction and environmental remediation.

Hawking radiation from a non-extremal black hole is known to be approximately Planckian. The thermal spectrum receives multiple corrections including greybody factors and due to kinematical restrictions on the infrared and ultraviolet frequencies. We show that another significant correction to the spectrum arises if the black hole is assumed to live in a thermal bath and the emitted radiation gets thermalised at the bath temperature. This modification reshapes the thermal spectrum, and leads to appreciable deviation from standard results including modification in the decay rate of black holes. We argue that this altered decay rate has significance for cosmology and, in a realistic setting, show that it alters the life time of primordial black holes (PBHs) in the early universe. In particular, the very light PBHs formed right after the end of inflation decay faster which may have interesting phenomenological implications., Comment: 6 pages and 2 figures

Koopman-based lifted linear identification have been widely used for data-driven prediction and model predictive control (MPC) of nonlinear systems. It has found applications in flow-control, soft robotics, and unmanned aerial vehicles (UAV). For autonomous systems, this system identification method works by embedding the nonlinear system in a higher-dimensional linear space and computing a finite-dimensional approximation of the corresponding Koopman operator with the Extended Dynamic Mode Decomposition (EDMD) algorithm. EDMD is a data-driven algorithm that estimates an approximate linear system by lifting the state data-snapshots via nonlinear dictionary functions. For control systems, EDMD is further modified to utilize both state and control data-snapshots to estimate a lifted linear predictor with control input. This article investigates how the estimation process is affected when the data is quantized. Specifically, we examine the fundamental connection between estimates of the linear predictor matrices obtained from unquantized data and those from quantized data via modified EDMD. Furthermore, using the law of large numbers, we demonstrate that, under a large data regime, the quantized estimate can be considered a regularized version of the unquantized estimate. We also explore the relationship between the two estimates in the finite data regime. We further analyze the effect of nonlinear lifting functions on this regularization due to quantization. The theory is validated through repeated numerical experiments conducted on several control systems. The effect of quantization on the MPC performance is also demonstrated., Comment: 15 pages, 4 figures. arXiv admin note: text overlap with arXiv:2410.02803

Electron glasses offer a convenient laboratory platform to study glassy dynamics. Traditionally, the interplay between long-range Coulomb interactions and disorder is deemed instrumental in stabilizing the electron glass phase. Existing experimental studies on electron glass have focused on doped semiconductors, strongly correlated systems, granular systems, etc., all of which are far from the well-delocalized limit. In this work, we expand the study of electron glasses to a well-known quantum paraelectric SrTiO$_3$ (STO) and unveil a new scenario: how naturally occurring ferroelastic twin walls of STO could result in glassy electrons, even in a metallic state. We show that the emergent two-dimensional electron gas at the $\gamma$-Al$_2$O$_3$/STO interface exhibits long-lasting temporal relaxations in resistance and memory effects at low temperatures, which are hallmarks of glassiness. We also demonstrate that the glass-like relaxations could be further tuned by application of an electric field. This implies that the observed glassy dynamics is connected with the development of polarity near the structural twin walls of STO and the complex interactions among them, arising from the coupling between ferroelastic and ferroelectric orders. The observation of this glassy metal phase not only extends the concept of electron glasses to metallic systems with multiple order parameters but also contributes to the growing understanding of the fascinating and diverse physical phenomena that emerge near the quantum critical point., Comment: 20 pages, 5 figures

The thermodynamic uncertainty relation (TUR) is a fundamental principle in non-equilibrium thermodynamics that relates entropy production to fluctuations in a system, establishing a trade-off between the precision of an observable and the thermodynamic cost. Investigating TUR violations challenges classical thermodynamic limits, offering the potential for improved precision-entropy trade-offs, which is crucial for enhancing performance and optimization in quantum technologies. In this work, we investigate the thermodynamic uncertainty relation within a quantum collisional model, which offers the advantage of discretizing interactions into successive collisions with auxiliaries, allowing for precise tracking of dynamics and the incorporation of memory effects and non-Markovian behavior. We consider three types of dynamics in the collisional model: one is Markovian evolution, achieved by taking the continuous time limit and imposing the stability condition, while the other two are non-Markovian dynamics - one arising from increasing the collision time between the system and the auxiliaries, and the other from incorporating interactions between the auxiliaries. For the Markovian dynamics, we examine the classical and quantum TUR bounds in the non-equilibrium steady-state regime, and also the finite-time TUR bound. We demonstrate that the classical TUR bound is violated once a certain threshold of collisions with the auxiliaries is exceeded, with the maximum violation observed at the steady state. For the two non-Markovian approaches, we find that the violation of the finite-time TUR bound is highly dependent on the type of non-Markovianity, warranting a detailed comparison., Comment: 17 Pages, 4 Figures

Star clusters, including high-mass stars, form within hub-filament systems (HFSs). Observations of HFSs that remain unaffected by feedback from embedded stars are rare yet crucial for understanding the mass inflow process in high-mass star formation. Using the JWST NIRCAM images, Dewangan et al. 2024, reported that the high-mass protostar G11P1 is embedded in a candidate HFS (G11P1-HFS; $<0.6$ pc). Utilizing ALMA N$_{2}$H$^{+}$(1-0) data, we confirm the presence of G11P1-HFS and study the dense gas kinematics. We analyzed the position-position-velocity (PPV) map and estimated on-sky velocity gradient ($V_g$) and gravity ($\mathcal{F}_{g}$) vectors. The spatial distribution of gas velocity and H$_2$ column density was examined. The steep $V_g$ of 5 km s$^{-1}$ pc$^{-1}$ and $-$7 km s$^{-1}$ pc$^{-1}$ toward either side of G11P1-hub, and the decreasing $V_g$ toward the hub, identify G11P1-HFS as a small-scale HFS in its nascent phase. $V_g$ and $\mathcal{F}_{g}$ align along the filaments, indicating gravity-driven flows. This work highlights the wiggled, funnel-shaped morphology of a HFS in PPV space, suggesting the importance of subfilaments or transverse gas flows in mass transportation to the hub., Comment: 10 pages, 11 figures, 1 table, Accepted for publication in A&A Letters

We present a multimethod investigation into the nature of the recently reported quantum spin liquid (QSL) phase in the spin-$1/2$ Heisenberg antiferromagnet on the Shastry-Sutherland lattice. A comprehensive projective symmetry group classification of fermionic mean-field Ans\"atze on this lattice yields 46 U(1) and 80 $\mathbb{Z}_{2}$ states. Motivated by density-matrix renormalization group (DMRG) calculations suggesting that the Shastry-Sutherland model and the square-lattice $J_{1}$-$J_{2}$ Heisenberg antiferromagnet putatively share the same QSL phase, we establish a mapping of our Ans\"atze to those of the square lattice. This enables us to identify the equivalent of the square-lattice QSL (Z2A$zz$13) in the Shastry-Sutherland system. Employing state-of-the-art variational Monte Carlo calculations with Gutzwiller-projected wavefunctions improved upon by Lanczos steps, we demonstrate the excellent agreement of energies and correlators between a gapless (Dirac) $\mathbb{Z}_{2}$ spin liquid -- characterized by only few parameters -- and approaches based on neural quantum states and DMRG. Furthermore, the real-space spin-spin correlations are shown to decay with the same power law as in the $J_{1}$-$J_{2}$ square lattice model, which also hosts a $\mathbb{Z}_{2}$ Dirac spin liquid. Finally, we apply the recently developed Keldysh formulation of the pseudo-fermion functional renormalization group to compute the dynamical spin structure factor; these correlations exhibit the features expected due to Dirac cones in the excitation spectrum, thus providing strong independent evidence for a Dirac QSL ground state. Our finding of a $d$-wave pairing $\mathbb{Z}_{2}$ Dirac QSL is consistent with the recently observed signatures of QSL behavior in Pr$_2$Ga$_2$BeO$_7$ and outlines predictions for future experiments., Comment: 36 pages, 18 figures, 12 tables

We present an observational study of the S284-RE region, a low-metallicity area associated with the extended S284 HII region. A thermally supercritical filament (mass $\sim$2402 $M_{\odot}$, length $\sim$8.5 pc) is investigated using the Herschel column density map. The Spitzer ratio 4.5 $\mu$m/3.6 $\mu$m map traces the H$_{2}$ outflows in this filament, where previously reported young stellar objects (YSOs) are spatially distributed. Analysis of the YSO distribution has revealed three active star-forming clusters (YCl1, YCl2, YCl3) within the filament. YCl3 seems to be the most evolved, YCl2 the youngest, while YCl1 displays signs of non-thermal fragmentation. The JWST (F470N+F444W)/F356W ratio map reveals at least seven bipolar H$_{2}$ outflows, with four (olc1--olc4) in YCl1 and three (ol1--ol3) in YCl2. The driving sources of these outflows are identified based on outflow geometry, ALMA continuum peaks, and YSO positions. Two ALMA continuum sources, #2 and #3, from the $M$-$R_{\rm eff}$ plot are recognized as potential massive star formation candidates. The ALMA continuum source #2 hosts at least three outflow-driving sources, whereas the ALMA continuum source #3 contains two. The bipolar outflow olc1, driven by an embedded object within the continuum source #2, is likely a massive protostar, as indicated by Br-$\alpha$ and PAH emissions depicted in the JWST (F405N+F444W)/F356W ratio map. The presence of H$_{2}$ knots in the outflows olc1 and ol1 suggests episodic accretion. Overall, the study investigates a massive protostar candidate, driving the $\sim$2.7 pc H$_{2}$ outflow olc1 and undergoing episodic accretion., Comment: Accepted for publication in The Astrophysical Journal, the manuscript consists of 19 pages, 8 figures, and 3 tables

Photonics/light localization techniques are important in understanding the structural changes in biological tissues at the nano- to sub-micron scale. It is now known that structural alteration starts at the nanoscale at the beginning of cancer progression. This study examines the molecular-specific nano-structural alterations of chronic alcoholism and probiotic effects on colon cancer using a mouse model of colon cancer. Confocal microscopy and mesoscopic light-scattering analysis are applied to quantify structural changes in DNA (chromatin), cytoskeleton, and ki-67 protein cells with appropriate staining dyes. We assessed alcohol-treated and azoxymethane (AOM) with dextran sulfate sodium (DSS)-induced colitis models, including ethanol (EtOH) and probiotic (L.Casei) treatments separately and together. The inverse participation ratio (IPR) technique was employed to quantify the degree of light localization to access the molecular-specific spatial structural disorder as a biomarker for cancer progression detection. Significant enhancement of cancer progression was observed in the alcohol-treated group, and probiotics treatment with alcohol showed partial reversal of these changes in colon cancer. The results underscore the potential of the IPR technique in detecting early structural changes in colon cancer, offering insights into the mitigating effects of probiotics on alcohol-induced enhancement of colon cancer., Comment: 17 pages, 8 figures

The light scattering experiment establishes a relationship between refractive index fluctuations and fractal dimension in weakly scattering tissue-like media. Based on the box-counting approach, an analytical model is developed and shows that the fractal dimension has a functional dependency on the structural disorder or refractive index fluctuation for short-range correlation and approximately linearly depends on each other for tissue-like media. Several parametric imaging systems can be connected using this approach. Further, tissue's weak multifractality optical scattering is explored using the box-counting method. It is shown that with a functional transformation, the distribution follows lognormal distributions., Comment: 1i pages, 8 figures

We present a fully analytical model of hybridization between magnon, and phonons observed experimentally in magneto-Raman scattering in van der Waals (vdW) antiferromagnets (AFM). Here, the representative material, FePS3, has been shown to be a quasi-two-dimensional-Ising antiferromagnet, with additional features of spin-phonon coupling in the Raman spectra emerging below the N\'eel temperature (TN) of approximately 120 K. Using magneto-Raman spectroscopy as an optical probe of magnetic structure, we show that one of these Raman-active modes in the magnetically ordered state is a magnon with a frequency of 3.7 THz (~ 122 cm-1). In addition, one magnon band and three phonon bands are coupled via the magneto-elastic coupling evidenced by anti-crossing in the complete spectra. We consider a simple model involving only in-plane nearest neighbor exchange couplings (designed to give rise to a similar magnetic structure) and perpendicular anisotropy in presence of an out-of-plane magnetic field. Exact diagonalization of the Hamiltonian leads to energy bands which show that the interaction term gives rise to avoided crossings between the hybridized magnon and phonon branches. Realizing magnon-phonon coupling in two-dimensional (2D) AFMs is important for the verification of the theoretical predictions on exotic quantum transport phenomena like spin-caloritronics, topological magnonics, etc., Comment: 5 pages, 2 figures

Let $f$ be a conformal (analytic and univalent) map defined on the open unit disk $\D$ of the complex plane $\IC$ that is continuous on the semi-circle $\partial \D^{+}=\{z\in\IC:|z|=1, {\rm{Im}}\,z>0\}$. The existence of a uniform upper bound for the ratio of the length of the image of the horizontal diameter $(-1,1)$ to the length of the image of $\partial \D^{+}$ under $f$ was proved by Gehring and Hayman. In this article, at first, we generalize this result by introducing a simple pole for $f$ in $\D$ and considering the ratio of the length of the image of the vertical diameter $I=\{z: {\rm{Re}}\,z=0; ~|{\rm{Im}}\,z|<1\}$ to the length of the image of the semi-circle $C'=\{z: |z|=1;~ {\rm{Re}}\,z<0\}$ under such $f$. Finally, we further generalize this result by replacing the vertical diameter $I$ with a hyperbolic geodesic symmetric with respect to the real line, and by replacing $C'$ with the corresponding arc of the unit circle passing through the point $-1$., Comment: 13 pages, submitted to a journal

Ionization or excitation resulting from the delayed response of the electron cloud to nuclear recoil is known as the Migdal effect. Dark matter searches utilizing this process set the most stringent bounds on the spin-independent dark matter-nucleon scattering cross section over a large region of the sub-GeV dark matter parameter space, underscoring its significance in dark matter detection. In this paper, we quantify the regions of dark matter parameter space that are challenging to probe via the Migdal effect due to the presence of dominant solar neutrino backgrounds for both liquid noble and semiconductor targets. Our findings reveal that there is no hard floor in the dark matter parameter space. Instead, we map the so called neutrino fog. In mapping the neutrino fog, we identify the importance of incorporating the Migdal effect induced by neutrinos, as well as neutrino-electron scattering and dominant coherent neutrino-nucleus scattering, particularly for semiconductor targets. Furthermore, we demonstrate that a large portion of the relic density allowed parameter space lies within the neutrino fog. Finally, we estimate the exposure required to detect neutrino induced Migdal events in direct detection experiments., Comment: 21 pages, 6 figures. Comments are welcome

We measure the branching fraction and $\it CP$-violating flavor-dependent rate asymmetry of $B^{0} \to \pi^{0} \pi^{0}$ decays reconstructed using the Belle II detector in an electron-positron collision sample containing $387 \times 10^{6}$ $B\overline{B}$ pairs. Using an optimized event selection, we find $126\pm 20$ signal decays in a fit to background-discriminating and flavor-sensitive distributions. The resulting branching fraction is $(1.25 \pm 0.23)\times 10^{-6}$ and the $\it CP$-violating asymmetry is $0.03 \pm 0.30$.

We analyze the phase transition between a symmetric metallic parent state and itinerant altermagnetic order. The underlying mechanism we reveal in our microscopic model of electrons on a Lieb lattice does not involve orbital ordering, but derives from sublattice interference., Comment: 7 pages, 3 figures, supplementary material

The hot and dense QCD matter, known as the Quark-Gluon Plasma (QGP), is explored through heavy-ion collision experiments at the LHC and RHIC. Jets and heavy flavors, produced from the initial hard scattering, are used as hard probes to study the properties of the QGP. Recent experimental observations on jet quenching and heavy-flavor suppression have strengthened our understanding, allowing for fine-tuning of theoretical models in hard probes. The second conference, HOT QCD Matter 2024, was organized to bring the community together for discussions on key topics in the field. This article comprises 15 sections, each addressing various aspects of hard probes in relativistic heavy-ion collisions, offering a snapshot of current experimental observations and theoretical advancements. The article begins with a discussion on memory effects in the quantum evolution of quarkonia in the quark-gluon plasma, followed by an experimental review, new insights on jet quenching at RHIC and LHC, and concludes with a machine learning approach to heavy flavor production at the Large Hadron Collider., Comment: Compilation of the 15 contributions in Hard Probes presented at the second 'Hot QCD Matter 2024 Conference' held from July 1-3, 2024, organized by IIT Mandi, India

Hybrid magnonics, exploring the coupling between magnons and quantum systems, is an exciting field for developing next-generation information technologies. Achieving a strong and tunable magnon-magnon coupling (MMC) in confined nanomagnets is crucial for the on-chip integration of these hybrid systems and advancing the field. In this work, we numerically investigate the interactions between different magnon modes excited within an elliptical magnonic nano-disc (EMND), demonstrating an anti-crossing effect in the dispersion spectra. A comprehensive theoretical framework was presented that explains this anti-crossing phenomenon as a result of MMC and provide estimates for the strength of the coupling (g). Furthermore, we show that this intermodal coupling can be tuned from a strong coupling regime (g = 300 MHz) to a weak coupling regime by varying the direction of the external magnetic field and the intrinsic properties of the EMND. Our combined numerical and theoretical findings offer new insights into MMC, significantly advancing the field of quantum magnonics and magnon-based quantum information technology., Comment: 24 pages, 5 figures, to be published in Journal of Applied Physics

Individual fairness guarantees are often desirable properties to have, but they become hard to formalize when the dataset contains outliers. Here, we investigate the problem of developing an individually fair $k$-means clustering algorithm for datasets that contain outliers. That is, given $n$ points and $k$ centers, we want that for each point which is not an outlier, there must be a center within the $\frac{n}{k}$ nearest neighbours of the given point. While a few of the recent works have looked into individually fair clustering, this is the first work that explores this problem in the presence of outliers for $k$-means clustering. For this purpose, we define and solve a linear program (LP) that helps us identify the outliers. We exclude these outliers from the dataset and apply a rounding algorithm that computes the $k$ centers, such that the fairness constraint of the remaining points is satisfied. We also provide theoretical guarantees that our method leads to a guaranteed approximation of the fair radius as well as the clustering cost. We also demonstrate our techniques empirically on real-world datasets., Comment: 12 pages

Large language models (LLMs) are powerful but resource intensive, limiting accessibility. HITgram addresses this gap by offering a lightweight platform for n-gram model experimentation, ideal for resource-constrained environments. It supports unigrams to 4-grams and incorporates features like context sensitive weighting, Laplace smoothing, and dynamic corpus management to e-hance prediction accuracy, even for unseen word sequences. Experiments demonstrate HITgram's efficiency, achieving 50,000 tokens/second and generating 2-grams from a 320MB corpus in 62 seconds. HITgram scales efficiently, constructing 4-grams from a 1GB file in under 298 seconds on an 8 GB RAM system. Planned enhancements include multilingual support, advanced smoothing, parallel processing, and model saving, further broadening its utility.

We consider a variant of the target defense problems where a group of defenders are tasked to simultaneously capture an intruder. The intruder's objective is to reach a target without being simultaneously captured by the defender team. Some of the defenders are sensing-limited and do not have any information regarding the intruder's position or velocity at any time. The defenders may communicate with each other using a connected communication graph. We propose a decentralized feedback strategy for the defenders, which transforms the simultaneous capture problem into a unique nonlinear consensus problem. We derive a sufficient condition for simultaneous capture in terms of the agents' speeds, sensing, and communication capabilities. The proposed decentralized controller is evaluated through extensive numerical simulations., Comment: Accepted for publication in the IEEE Control Systems Letters (L-CSS)

We report a sequential two-step vapor deposition process for growing mixed-dimensional van der Waals (vdW) materials, specifically Te nanowires (1D) and MoS$_2$ (2D), on a single SiO$_2$ wafer. Our growth technique offers a unique potential pathway to create large scale, high-quality, defect-free interfaces. The assembly of samples serves a twofold application: first, the as-prepared heterostructures (Te NW/MoS$_2$) provide insights into the atomically thin depletion region of a 1D/2D vdW diode, as revealed by electrical transport measurements and density functional theory-based quantum transport calculations. The charge transfer at the heterointerface is confirmed using Raman spectroscopy and Kelvin probe force microscopy (KPFM). We also observe modulation of the rectification ratio with varying applied gate voltage. Second, the non-hybrid regions on the substrate, consisting of the as-grown individual Te nanowires and MoS$_2$ microstructures, are utilized to fabricate separate p- and n-FETs, respectively. Furthermore, the ionic liquid gating helps to realize low-power CMOS inverter and all basic logic gate operations using a pair of n- and p- field-effect transistors (FETs) on Si/SiO$_2$ platform. This approach also demonstrates the potential for unifying diode and CMOS circuits on a single platform, opening opportunities for integrated analog and digital electronics.

A multi-wavelength, multi-scale study of the Mon R2 hub-filament system (HFS) reveals a spiral structure, with the central hub containing more mass than its filaments. ALMA C$^{18}$O(1-0) emission reveals several accreting filaments connected to a molecular ring (size $\sim$0.18 pc $\times$ 0.26 pc). The molecular ring surrounds the infrared (IR) ring (size $\sim$0.12 pc $\times$ 0.16 pc), which is not usually observed. The IR ring encircles IR dark regions and a population of embedded near-IR sources, including the massive stars IRS 1 and IRS 2. ALMA HNC(3-2) line data reveal a mirrored B-shaped feature (extent $\sim$19000 AU $\times$ 39000 AU) toward the eastern part of the molecular ring, suggesting expansion at $\sim$2.25 km s$^{-1}$. Distinct HNC sub-structures in both redshifted and blueshifted velocity components are investigated toward the B-shaped feature. The presence of these braid-like substructures in each velocity component strongly suggests instability in photon-dominated regions. A dusty shell-like feature (extent $\sim$0.04 pc $\times$ 0.07 pc; mass $\sim$7 M$_{\odot}$) hosting IRS 1 is identified in the ALMA 1.14 mm continuum map, centered toward the base of the B-shaped feature. The IR and dense molecular rings are likely shaped by feedback from massive stars, driven by high pressure values between 10$^{-8}$-10$^{-10}$ dynes cm$^{-2}$, observed within a 1 pc range of the B0 ZAMS star powering the ultracompact HII region. Overall, these outcomes support that the Mon R2 HFS transitioned from IR-quiet to IR-bright, driven by the interaction between gas accretion and feedback from massive stars., Comment: Accepted for publication in The Astronomical Journal, the manuscript consists of 23 pages, 12 figures, and 2 tables

The reliability of clinical trial outcomes is crucial, especially in guiding medical decisions. In this paper, we introduce the Fragility Index (FI) for time-to-event endpoints in single-arm clinical trials - a novel metric designed to quantify the robustness of study conclusions. The FI represents the smallest number of censored observations that, when reclassified as uncensored events, causes the posterior probability of the median survival time exceeding a specified threshold to fall below a predefined confidence level. While drug effectiveness is typically assessed by determining whether the posterior probability exceeds a specified confidence level, the FI offers a complementary measure, indicating how robust these conclusions are to potential shifts in the data. Using a Bayesian approach, we develop a practical framework for computing the FI based on the exponential survival model. To facilitate the application of our method, we developed an R package fi, which provides a tool to compute the Fragility Index. Through real world case studies involving time to event data from single arms clinical trials, we demonstrate the utility of this index. Our findings highlight how the FI can be a valuable tool for assessing the robustness of survival analyses in single-arm studies, aiding researchers and clinicians in making more informed decisions., Comment: 17 pages, 3 figures

In this paper, we have studied the effects of holographic dark energy on the evolution of gravitational waves. The background evolution of gravitational waves in a flat FRW universe is considered and studied in the presence of various holographic dark energy models. The perturbation equations governing the evolution of the gravitational waves have been constructed and solutions are obtained. These solutions are studied in detail to get a proper understanding of the characteristics of the gravitational waves in the presence of holographic dark energy. The work can be a significant tool in studying different dark energy models comparatively using the features of the gravitational wave evolution., Comment: 16 pages, 7 figures

Thermal Hall transport has emerged as a valuable tool for probing the fractionalized excitations in chiral quantum spin liquids. Observing quantized thermal Hall response, expected at temperatures below the spectral gap, has been challenging and controversial. The finite temperature behavior, especially in the quantum critical regime above the spectral gap, can provide useful signatures of the underlying topological order. In this context, we study the spin-$1/2$ Heisenberg antiferromagnet on a kagome lattice that is believed to be a U$(1)$ Dirac spin liquid over a wide intermediate energy range. Scalar spin chirality perturbations turn this into a gapped abelian chiral spin liquid (CSL) with semionic topological order. Using a recently developed large-$N$ technique [Guo et al., Phys. Rev. B 101, 195126 (2020)], we obtain explicit expressions for the thermal Hall conductivity $\kappa_{xy}$ at finite temperatures taking into account both matter and gauge fluctuations. At low temperatures below the spectral gap, the quantized thermal Hall response agrees with that expected from conformal field theory and gravitational anomaly arguments. Our main finding is that in a large temperature window spanning the spectral gap and the Curie temperature scales where quantum critical fluctuations dominate, $\kappa_{xy}/T$ obeys a power-law with logarithmic corrections. Our analysis also provides a route to understanding the thermal Hall response at temperatures in the quantum critical regime of other spin liquid phases., Comment: 29 pages, 12 figures

Hub-filament systems (HFSs) are potential sites of massive star formation (MSF). To understand the role of filaments in MSF and the origin of HFSs, we conducted a multi-scale and multi-wavelength observational investigation of the molecular cloud G321.93-0.01. The $^{13}$CO($J$ = 2-1) data reveal multiple HFSs, namely, HFS-1, HFS-2, and a candidate HFS (C-HFS). HFS-1 and HFS-2 exhibit significant mass accretion rates ($\dot{M}_{||}$ $> 10^{-3}$ $M_{\odot}$ yr$^{-1}$) to their hubs (i.e., Hub-1 and Hub-2, respectively). Hub-1 is comparatively massive, having higher $\dot{M}_{||}$ than Hub-2, allowing to derive a relationship $\dot{M}_{||} \propto M^{\beta}_{\rm{hub}}$, with $\beta \sim1.28$. Detection of three compact HII regions within Hub-1 using MeerKAT 1.28 GHz radio continuum data and the presence of a clump (ATL-3), which meets Kauffmann & Pillai's criteria for MSF, confirm the massive star-forming activity in HFS-1. We find several low-mass ALMA cores (1-9 $M_{\odot}$) inside ATL-3. The presence of a compact HII region at the hub of C-HFS confirms that it is active in MSF. Therefore, HFS-1 and C-HFS are in relatively evolved stages of MSF, where massive stars have begun ionizing their surroundings. Conversely, despite a high $\dot{M}_{||}$, the non-detection of radio continuum emission toward Hub-2 suggests it is in the relatively early stages of MSF. Analysis of $^{13}$CO($J$ = 2-1) data reveals that the formation of HFS-1 was likely triggered by the collision of a filamentary cloud about 1 Myr ago. In contrast, the relative velocities ($\gtrsim 1$ km s$^{-1}$) among the filaments of HFS-2 and C-HFS indicate their formation through the merging of filaments., Comment: Accepted for publication in The Astronomical Journal, the manuscript consists of 27 pages, 11 figures, and 5 tables

We report measurements of the absolute branching fractions $\mathcal{B}(B_s^0 \to D_s^{\pm} X)$, $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X)$, and $\mathcal{B}(B_s^0 \to D^{\pm} X)$, where the latter is measured for the first time. The results are based on a 121.4\,fb$^{-1}$ data sample collected at the $\Upsilon(10860)$ resonance by the Belle detector at the KEKB asymmetric-energy $e^+ e^-$ collider. We reconstruct one $B_s^0$ meson in $e^+e^- \to \Upsilon(10860) \to B_s^{*} \bar{B}_s^{*}$ events and measure yields of $D_s^+$, $D^0$, and $D^+$ mesons in the rest of the event. We obtain $\mathcal{B}(B_s^0 \to D_s^{\pm} X) = (68.6 \pm 7.2 \pm 4.0)\%$, $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X) = (21.5 \pm 6.1 \pm 1.8)\%$, and $\mathcal{B}(B_s^0 \to D^{\pm} X) = (12.6 \pm 4.6 \pm 1.3)\%$, where the first uncertainty is statistical and the second is systematic. Averaging with previous Belle measurements gives $\mathcal{B}(B_s^0 \to D_s^{\pm} X) = (63.4 \pm 4.5 \pm 2.2)\%$ and $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X) = (23.9 \pm 4.1 \pm 1.8)\%$. For the $B_s^0$ production fraction at the $\Upsilon(10860)$, we find $f_s = (21.4^{+1.5}_{-1.7})\%$., Comment: 23 pages, 9 figures, submitted to JHEP

We present measurements of $B \to K{}^{*}(892)\gamma$ decays using $365\,{\rm fb}^{-1}$ of data collected from 2019 to 2022 by the Belle~II experiment at the SuperKEKB asymmetric-energy $e^+e^-$ collider. The data sample contains $(387 \pm 6) \times 10^6$ $B\overline{B}$ events. We measure branching fractions ($\mathcal{B}$) and $C\!P$ asymmetries ($\mathcal{A}_{C\!P}$) for both $B^{0}\to K{}^{*0}\gamma$ and $B^{+}\to K{}^{*+}\gamma$ decays. The difference in $C\!P$ asymmetries ($\Delta \mathcal{A}_{C\!P}$) and the isospin asymmetry ($\Delta_{0+}$) between these neutral and charged channels are also measured. We obtain the following branching fractions and $C\!P$ asymmetries: $\mathcal{B} (B^{0} \to K{}^{*0}\gamma) = (4.14 \pm 0.10 \pm 0.11 ) \times 10^{-5}$, $\mathcal{B} (B^{+} \to K{}^{*+}\gamma) = (4.02 \pm 0.13 \pm 0.13 )\times 10^{-5}$, $\mathcal{A}_{C\!P} (B^{0} \to K{}^{*0}\gamma) = (-3.3 \pm 2.3 \pm 0.4 )\%$, and $\mathcal{A}_{C\!P} (B^{+} \to K{}^{*+}\gamma) = (-0.7 \pm 2.9 \pm 0.6 )\%$. The measured difference in $C\!P$ asymmetries is $\Delta \mathcal{A}_{C\!P} = (+2.6 \pm 3.8 \pm 0.7 )\%$, and the measured isospin asymmetry is $\Delta_{0+} = (+5.0 \pm 2.0 \pm 1.5 )\%$. The first uncertainties listed are statistical and the second are systematic. These results are consistent with world-average values and theory predictions.

We consider the adjoint action of the symplectic Lie group $\mathrm{Sp}(2n,\mathbb{C})$ on its Lie algebra $\mathfrak{sp}(2n,\mathbb{C})$. An element $X \in \mathfrak{sp}(2n,\mathbb{C})$ is called $\mathrm{Ad}_{\mathrm{Sp}(2n,\mathbb{C})}$-real if $ -X = \mathrm{Ad}(g)X$ for some $g \in \mathrm{Sp}(2n,\mathbb{C})$. Moreover, if $ -X = \mathrm{Ad}(h)X $ for some involution $h \in \mathrm{Sp}(2n,\mathbb{C})$, then $X \in \mathfrak{sp}(2n,\mathbb{C})$ is called strongly $\mathrm{Ad}_{\mathrm{Sp}(2n,\mathbb{C})}$-real. In this paper, we prove that for every element $X \in \mathfrak{sp}(2n,\mathbb{C})$, there exists a skew-involution $g \in \mathrm{Sp}(2n,\mathbb{C})$ such that $-X =\mathrm{Ad}(g)X$. Furthermore, we classify the strongly $\mathrm{Ad}_{\mathrm{Sp}(2n,\mathbb{C})}$-real elements in $\mathfrak{sp}(2n,\mathbb{C})$. We also classify skew-Hamiltonian matrices that are similar to their negatives via a symplectic involution., Comment: 9 pages, Final version, To appear in Linear Algebra and its Applications

Two-dimensional (2D) transition metal di-chalcogenide layers with high electrical conductivity and spin-orbit coupling (SOC) can find huge potential in spintronic devices. With limited success of 2D spin Hall material development, we demonstrate vanadium (V) substitutionally doped monolayer MoS2 (VMS) as a potential spin Hall material having tunable electrical conductivity, SOC strength, and room temperature magnetism. Systematic enhancement in the electrical conductivity is observed with the extent of V doping, where it is enhanced from ~0.3 S/m of MoS2 to ~100000 S/m upon doping to the level of 9 atomic%. Ferromagnetic resonance (FMR) based spin-pumping experiments indicate the spin transport across the junction of permalloy (Py) and VMS. Spin-torque FMR measurements demonstrate the suggesting latter's potential as a spin-orbit torque layer in 2D spintronic devices.

The widespread use of social media platforms like Twitter and Facebook has enabled people of all ages to share their thoughts and experiences, leading to an immense accumulation of user-generated content. However, alongside the benefits, these platforms also face the challenge of managing hate speech and offensive content, which can undermine rational discourse and threaten democratic values. As a result, there is a growing need for automated methods to detect and mitigate such content, especially given the complexity of conversations that may require contextual analysis across multiple languages, including code-mixed languages like Hinglish, German-English, and Bangla. We participated in the English task where we have to classify English tweets into two categories namely Hate and Offensive and Non Hate-Offensive. In this work, we experiment with state-of-the-art large language models like GPT-3.5 Turbo via prompting to classify tweets into Hate and Offensive or Non Hate-Offensive. In this study, we evaluate the performance of a classification model using Macro-F1 scores across three distinct runs. The Macro-F1 score, which balances precision and recall across all classes, is used as the primary metric for model evaluation. The scores obtained are 0.756 for run 1, 0.751 for run 2, and 0.754 for run 3, indicating a high level of performance with minimal variance among the runs. The results suggest that the model consistently performs well in terms of precision and recall, with run 1 showing the highest performance. These findings highlight the robustness and reliability of the model across different runs., Comment: Accepted at FIRE 2024 (Track: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages (HASOC)). arXiv admin note: text overlap with arXiv:2411.05039, arXiv:2411.06946

Electron-magnon coupling reveals key insights into the interfacial properties between non-magnetic metals and magnetic insulators, influencing charge transport and spin dynamics. Here, we present temperature-dependent Raman spectroscopy and magneto-transport measurements of few-layer graphene (FLG)/antiferromagnetic FePS\(_3\) heterostructures. The magnon mode in FePS\(_3\) softens below 40 K, and effective magnon stiffness decreases with cooling. Magnetotransport measurements show that FLG exhibits negative magnetoresistance (MR) in the heterostructure at low fields (\(\pm 0.2 \, \text{T}\)), persisting up to 100 K; beyond this, MR transitions to positive. Notably, as layer thickness decreases, the coupling strength at the interface reduces, leading to a suppression of negative MR. Additionally, magnetodielectric measurements in the FLG/FePS\(_3\)/FLG heterostructure show an upturn at temperatures significantly below ($T_\text{N}$), suggesting a role for the magnon mode in capacitance, as indicated by hybridization between magnon and phonon bands in pristine FePS\(_3\) \textit{via} magnetoelastic coupling.

Often in prediction tasks, the predictive model itself can influence the distribution of the target variable, a phenomenon termed performative prediction. Generally, this influence stems from strategic actions taken by stakeholders with a vested interest in predictive models. A key challenge that hinders the widespread adaptation of performative prediction in machine learning is that practitioners are generally unaware of the social impacts of their predictions. To address this gap, we propose a methodology for learning the distribution map that encapsulates the long-term impacts of predictive models on the population. Specifically, we model agents' responses as a cost-adjusted utility maximization problem and propose estimates for said cost. Our approach leverages optimal transport to align pre-model exposure (ex ante) and post-model exposure (ex post) distributions. We provide a rate of convergence for this proposed estimate and assess its quality through empirical demonstrations on a credit-scoring dataset.

The rapid growth of social media has resulted in an large volume of user-generated content, particularly in niche domains such as cryptocurrency. This task focuses on developing robust classification models to accurately categorize cryptocurrency-related social media posts into predefined classes, including but not limited to objective, positive, negative, etc. Additionally, the task requires participants to identify the most relevant answers from a set of posts in response to specific questions. By leveraging advanced LLMs, this research aims to enhance the understanding and filtering of cryptocurrency discourse, thereby facilitating more informed decision-making in this volatile sector. We have used a prompt-based technique to solve the classification task for reddit posts and twitter posts. Also, we have used 64-shot technique along with prompts on GPT-4-Turbo model to determine whether a answer is relevant to a question or not., Comment: Accepted at FIRE 2024 (Track: Opinion Extraction and Question Answering from CryptoCurrency-Related Tweets and Reddit posts (CryptOQA))

Gastrointestinal (GI) tract cancers account for a substantial portion of the global cancer burden, where early diagnosis is critical for improved management and patient outcomes. The complex aetiologies and overlapping symptoms across GI cancers often delay diagnosis, leading to suboptimal treatment strategies. Cancer-related queries are crucial for timely diagnosis, treatment, and patient education, as access to accurate, comprehensive information can significantly influence outcomes. However, the complexity of cancer as a disease, combined with the vast amount of available data, makes it difficult for clinicians and patients to quickly find precise answers. To address these challenges, we leverage large language models (LLMs) such as GPT-3.5 Turbo to generate accurate, contextually relevant responses to cancer-related queries. Pre-trained with medical data, these models provide timely, actionable insights that support informed decision-making in cancer diagnosis and care, ultimately improving patient outcomes. We calculate two metrics: A1 (which represents the fraction of entities present in the model-generated answer compared to the gold standard) and A2 (which represents the linguistic correctness and meaningfulness of the model-generated answer with respect to the gold standard), achieving maximum values of 0.546 and 0.881, respectively., Comment: Accepted at FIRE 2024 (Track: Conversational System for Differential Diagnosis of GI Cancer)

Code-mixing, the integration of lexical and grammatical elements from multiple languages within a single sentence, is a widespread linguistic phenomenon, particularly prevalent in multilingual societies. In India, social media users frequently engage in code-mixed conversations using the Roman script, especially among migrant communities who form online groups to share relevant local information. This paper focuses on the challenges of extracting relevant information from code-mixed conversations, specifically within Roman transliterated Bengali mixed with English. This study presents a novel approach to address these challenges by developing a mechanism to automatically identify the most relevant answers from code-mixed conversations. We have experimented with a dataset comprising of queries and documents from Facebook, and Query Relevance files (QRels) to aid in this task. Our results demonstrate the effectiveness of our approach in extracting pertinent information from complex, code-mixed digital conversations, contributing to the broader field of natural language processing in multilingual and informal text environments. We use GPT-3.5 Turbo via prompting alongwith using the sequential nature of relevant documents to frame a mathematical model which helps to detect relevant documents corresponding to a query., Comment: Accepted at FIRE 2024 (Track: Code-Mixed Information Retrieval from Social Media Data)

Sarcasm detection is a significant challenge in sentiment analysis, particularly due to its nature of conveying opinions where the intended meaning deviates from the literal expression. This challenge is heightened in social media contexts where code-mixing, especially in Dravidian languages, is prevalent. Code-mixing involves the blending of multiple languages within a single utterance, often with non-native scripts, complicating the task for systems trained on monolingual data. This shared task introduces a novel gold standard corpus designed for sarcasm and sentiment detection within code-mixed texts, specifically in Tamil-English and Malayalam-English languages. The primary objective of this task is to identify sarcasm and sentiment polarity within a code-mixed dataset of Tamil-English and Malayalam-English comments and posts collected from social media platforms. Each comment or post is annotated at the message level for sentiment polarity, with particular attention to the challenges posed by class imbalance, reflecting real-world scenarios.In this work, we experiment with state-of-the-art large language models like GPT-3.5 Turbo via prompting to classify comments into sarcastic or non-sarcastic categories. We obtained a macro-F1 score of 0.61 for Tamil language. We obtained a macro-F1 score of 0.50 for Malayalam language., Comment: Accepted at FIRE 2024 (Track: Sarcasm Identification of Dravidian Languages Tamil & Malayalam (DravidianCodeMix))